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Chongjun Ouyang

Publications and source records attributed to Chongjun Ouyang.

At least 109 records · Page 6Linked to original sources

Revealing the Impact of Beamforming in ISAC

This letter proposes advanced beamforming design and analyzes its influence on the sensing and communications (S&C) performance for a multiple-antenna integrated S&C (ISAC) system with a single communication user and a single target. Novel closed-form beamformers are derived for three typical scenarios, including the sensing-centric design, communications-centric design, and Pareto optimal design. Regarding each scenario, the outage probability, ergodic communication rate (CR), and sensing rate (SR) are analyzed to derive the diversity orders and high signal-to-noise ratio slopes. Numerical results are provided to demonstrate that i) beamforming design can affect the high-SNR power offset and diversity order but does not influence the high-SNR slope; ii) ISAC exhibits larger high-SNR slopes and a more extensive SR-CR region than conventional frequency-division S&C (FDSAC) techniques.

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Joint Antenna Selection and Beamforming for Massive MIMO-enabled Over-the-Air Federated Learning

Over-the-air federated learning (OTA-FL) is an emerging technique to reduce the computation and communication overload at the PS caused by the orthogonal transmissions of the model updates in conventional federated learning (FL). This reduction is achieved at the expense of introducing aggregation error that can be efficiently suppressed by means of receive beamforming via large array-antennas. This paper studies OTA-FL in massive multiple-input multiple-output (MIMO) systems by considering a realistic scenario in which the edge server, despite its large antenna array, is restricted in the number of radio frequency (RF)-chains. For this setting, the beamforming for over-the-air model aggregation needs to be addressed jointly with antenna selection. This leads to an NP-hard problem due to the combinatorial nature of the optimization. We tackle this problem via two different approaches. In the first approach, we use the penalty dual decomposition (PDD) technique to develop a two-tier algorithm for joint antenna selection and beamforming. The second approach interprets the antenna selection task as a sparse recovery problem and develops two iterative joint algorithms based on the Lasso and fast iterative soft-thresholding methods. Convergence and complexity analysis is presented for all the schemes. The numerical investigations depict that the algorithms based on the sparse recovery techniques outperform the PDD-based algorithm, when the number of RF-chains at the edge server is much smaller than its array size. However, as the number of RF-chains increases, the PDD approach starts to be superior. Our simulations further depict that learning performance with all the antennas being active at the PS can be closely tracked by selecting less than 20% of the antennas at the PS.

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Revealing the Impact of SIC in NOMA-ISAC

The impact of successive interference cancellation (SIC) in non-orthogonal multiple access integrated sensing and communications (NOMA-ISAC) is analyzed. A two-stage SIC-based framework is proposed to deal with the inter-communication user and inter-functionality interferences. The performance of sensing and communications (S\&C) is analyzed for two SIC orders, i.e., the communications-centric SIC and the sensing-centric SIC. For each design, diversity orders, high signal-to-noise ratio (SNR) slopes, and high-SNR power offsets of the sensing rate (SR) and communication rate (CR) are derived as insights. Analytical results indicate that i) the main influence of SIC order on the SR and CR lies in the high-SNR power offsets; ii) ISAC provides more degrees of freedom than frequency-division S\&C (FDSAC). Numerical results show that the SR-CR region of ISAC entirely covers that of FDSAC.

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MIMO-ISAC: Performance Analysis and Rate Region Characterization

This article analyzes the performance of sensing and communications (S\&C) achieved by a multiple-input multiple-output downlink integrated S\&C (ISAC) system. Three ISAC scenarios are analyzed, including the sensing-centric design, communications-centric design, and Pareto optimal design. For each scenario, diversity orders and high signal-to-noise ratio slopes of the sensing rate (SR) and communication rate (CR) are derived to gain further insights. Numerical results reveal that \romannumeral1) ISAC achieves the same diversity order as existing frequency-division S\&C (FDSAC) techniques; \romannumeral2) ISAC achieves larger high-SNR slopes and a broader SR-CR region than FDSAC.

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Statistical-CSI-Based Antenna Selection and Precoding in Uplink MIMO

Classical antenna selection schemes require instantaneous channel state information (CSI). This leads to high signaling overhead in the system. This work proposes a novel joint receive antenna selection and precoding scheme for multiuser multiple-input multiple-output uplink transmission that relies only on the long-term statistics of the CSI. The proposed scheme designs the switching network and the uplink precoders, such that the expected throughput of the system in the long term is maximized. Invoking results from the random matrix theory, we derive a closed-form expression for the expected throughput of the system. We then develop a tractable iterative algorithm to tackle the throughput maximization problem, capitalizing on the alternating optimization and majorization-maximization (MM) techniques. Numerical results substantiate the efficiency of the proposed approach and its superior performance as compared with the baseline.

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Joint Receive Antenna Selection and Beamforming in RIS-Aided MIMO Systems

This work studies a low-complexity design for reconfigurable intelligent surface (RIS)-aided multiuser multiple-input multiple-output systems. The base station (BS) applies receive antenna selection to connect a subset of its antennas to the available radio frequency chains. For this setting, the BS switching network, uplink precoders, and RIS phase-shifts are jointly designed, such that the uplink sum-rate is maximized. The principle design problem reduces to an NP-hard mixed-integer optimization. We hence invoke the weighted minimum mean squared error technique and the penalty dual decomposition method to develop a tractable iterative algorithm that approximates the optimal design effectively. Our numerical investigations verify the efficiency of the proposed algorithm and its superior performance as compared with the benchmark.

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On the Ergodic Mutual Information of Keyhole MIMO Channels With Finite-Alphabet Inputs

This letter studies the ergodic mutual information (EMI) of keyhole multiple-input multiple-output channels having finite-alphabet input signals. The EMI is first investigated for single-stream transmission considering both cases with and without the channel state information at the transmitter. Then, the derived results are extended to the scenario of multi-stream transmission. Asymptotic analyses are performed in the regime of high signal-to-noise ratio (SNR). The high-SNR EMI is shown to converge to a constant with its rate of convergence determined by the diversity order. On this basis, the influence of the keyhole effect on the EMI is discussed. The analytical results are validated by numerical simulations.

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On the Ergodic Capacity of Reconfigurable Intelligent Surface (RIS)-Aided MIMO Channels

Reconfigurable intelligent surfaces (RISs) have emerged as a promising technique to enhance the system spectral efficiency. This paper investigates the ergodic channel capacity (ECC) of an RIS-aided multiple-input multiple-output channel under the assumption that the transmitter-RIS, RIS-receiver, and transmitter-receiver channels contain deterministic line-of-sight paths. Novel expressions are derived to characterize the upper and lower bounds of the ECC. To unveil more system insights, asymptotic analyses are performed to the system ECC in the limit of large signal-to-noise ratio (SNR) and number of reflecting elements (REs). Theoretical analyses suggest that the RIS's deployment can shape the ECC curve by influencing its high-SNR power offset and the ECC can get improved by increasing the number of REs.

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Capacity Scaling Law in Massive MIMO with Antenna Selection

Antenna selection is capable of handling the cost and complexity issues in massive multiple-input multiple-output (MIMO) channels. The sum-rate capacity of a multiuser massive MIMO uplink channel is characterized under the Nakagami fading. A mathematically tractable sum-rate capacity upper bound is derived for the considered system. Moreover, for a sufficiently large base station (BS) antenna number, a deterministic equivalent (DE) of the sum-rate bound is derived. Based on this DE, the sum-rate capacity is shown to grow double logarithmically with the number of BS antennas. The validity of the analytical result is confirmed by numerical experiments.

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Integrated Sensing and Communications: A Mutual Information-Based Framework

Integrated sensing and communications (ISAC) is potentially capable of circumventing the limitations of existing frequency-division sensing and communications (FDSAC) techniques. Hence, it has recently attracted significant attention. This article aims to propose a unified analytical framework for ISAC from a mutual information (MI) perspective. Based on the proposed framework, the sensing performance and the communication performance are evaluated by the sensing MI and the communication MI, respectively. The unity of this framework is originated from the fact that the sensing and communication (S\&C) performance metrics, i.e., the S\&C MI, have the similar physical and mathematical properties as well as the same unit of measurement. Based on this framework, the S\&C performance of downlink and uplink ISAC systems is investigated and compared with that of FDSAC systems. Along each considered system settings, numerical results are provided to demonstrate the superiority of ISAC over conventional FDSAC designs. Finally, promising open research directions are provided in the context of MI-based ISAC.

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Lens Antenna Arrays-Assisted mmWave MU-MIMO Uplink Transmission: Joint Beam Selection and Phase-Only Beamforming Design

This paper considers a lens antenna array-assisted millimeter wave (mmWave) multiuser multiple-input multiple-output (MU-MIMO) system. The base station's beam selection matrix and user terminals' phase-only beamformers are jointly designed with the aim of maximizing the uplink sum rate. In order to deal with the formulated mixed-integer optimization problem, a penalty dual decomposition (PDD)-based iterative algorithm is developed via capitalizing on the weighted minimum mean square error (WMMSE), block coordinate descent (BCD), and minorization-maximization (MM) techniques. Moreover, a low-complexity sequential optimization (SO)-based algorithm is proposed at the cost of a slight sum rate performance loss. Numerical results demonstrate that the proposed methods can achieve higher sum rates than state-of-the-art methods.

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Some Discussions on PHY Security in DF Relay

Physical layer (PHY) security in decode-and-forward (DF) relay systems is discussed. Based on the types of wiretap links, the secrecy performance of three typical secure DF relay models is analyzed. Different from conventional works in this field, rigorous derivations of the secrecy channel capacity are provided from an information-theoretic perspective. Meanwhile, closed-form expressions are derived to characterize the secrecy outage probability (SOP). For the sake of unveiling more system insights, asymptotic analyses are performed on the SOP for a sufficiently large signal-to-noise ratio (SNR). The analytical results are validated by computer simulations and are in excellent agreement.

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Performance of Downlink and Uplink Integrated Sensing and Communications (ISAC) Systems

This letter analyzes the fundamental performance of integrated sensing and communications (ISAC) systems. For downlink and uplink ISAC, the diversity orders are analyzed to evaluate the communication rate (CR) and the high signal-to-noise ratio (SNR) slopes are unveiled for the CR as well as the sensing rate (SR). Furthermore, the achievable downlink and uplink CR-SR regions are characterized. It is shown that ISAC can provide more degrees of freedom for both the CR and the SR than conventional frequency-division sensing and communications systems where isolated frequency bands are used for sensing and communications, respectively.

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How Should IRSs Scale to Harden Multi-Antenna Channels?

This work extends the concept of channel hardening to multi-antenna systems that are aided by intelligent reflecting surfaces (IRSs). For fading links between a multi-antenna transmitter and a single-antenna receiver, we derive an accurate approximation for the distribution of the input-output mutual information when the number of reflecting elements grows large. The asymptotic results demonstrate that by increasing the number of elements on the IRS, the end-to-end channel hardens as long as the physical dimensions of the IRS grow as well. The growth rate however need not to be of a specific order and can be significantly sub-linear. The validity of the analytical result is confirmed by numerical experiments.

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On the Performance of Uplink ISAC Systems

This letter analyzes the performance of uplink integrated sensing and communications (ISAC) systems where communication users (CUs) and radar targets (RTs) share the same frequency band. A non-orthogonal multiple access (NOMA) protocol is adopted in the communication procedure of the ISAC system. Novel expressions are derived to characterize the outage probability, ergodic communication rate, and sensing rate. Besides, the diversity order and high signal-to-noise ratio (SNR) slope are unveiled to gain further insights. It is found that when achieving the same communication rate, the ISAC system enjoys a higher sensing rate than the conventional frequency-division sensing and communications (FDSAC) system where CUs and RTs share isolated bands. All the results are validated by numerical simulations and are in excellent agreement.

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NOMA-ISAC: Performance Analysis and Rate Region Characterization

This paper analyzes the performance of a multiuser integrated sensing and communications (ISAC) system, where nonorthogonal multiple access (NOMA) is exploited to mitigate inter-user interference. Closed-form expressions are derived to evaluate the outage probability, ergodic communication rate, and sensing rate. Furthermore, asymptotic analyses are carried out to unveil diversity orders and high signal-to-noise ratio (SNR) slopes of the considered NOMA-ISAC system. As the further advance, the achievable sensing-communication rate region of ISAC is characterized. It is proved that ISAC system is capable of achieving a larger rate region than the conventional frequency-division sensing and communications (FDSAC) system.

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Channel Hardening of IRS-Aided Multi-Antenna Systems: How Should IRSs Scale?

Unlike active array antennas, intelligent reflecting surfaces (IRSs) are efficiently implemented at large dimensions. This allows for traceable realizations of large-scale IRS-aided MIMO systems in which not necessarily the array antennas, but the passive IRSs are large. It is widely believed that large IRS-aided MIMO settings maintain the fundamental features of massive MIMO systems, and hence they are the implementationally feasible technology for establishing the performance of large-scale MIMO settings. This work gives a rigorous proof to this belief. We show that using a large passive IRS, the end-to-end MIMO channel between the transmitter and the receiver always hardens, even if the IRS elements are strongly correlated. For the fading direct and reflection links between the transmitter and the receiver, our derivations demonstrate that as the number of IRS elements grows large, the capacity of end-to-end channel converges in distribution to a real-valued Gaussian random variable whose variance goes to zero. The order of this drop depends on how the physical dimensions of the IRS grow. We derive this order explicitly. Numerical experiments depict that the analytical asymptotic distribution almost perfectly matches the histogram of the capacity, even in practical scenarios. As a sample application of the results, we use the asymptotic characterization to study the dimensional trade-off between the transmitter and the IRS. The result is intuitive: For a given target performance, the larger the IRS is, the less transmit antennas are required to achieve the target. For an arbitrary ergodic and outage performance, we characterize this trade-off analytically. Our investigations demonstrate that using a practical IRS size, the target performance can be achieved with significantly small end-to-end MIMO dimensions.

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MMSE Bound for MIMO Channel

Detailed derivations of two bounds of the minimum mean-square error (MMSE) of complex-valued multiple-input multiple-output (MIMO) systems are proposed for performance evaluation. Particularly, the lower bound is derived based on a genie-aided MMSE estimator, whereas the upper bound is derived based on a maximum-likelihood (ML) estimator. Using the famous relationship between the mutual information (MI) and MMSE, two bounds for the MI are also derived, based on which we discuss the asymptotic behaviours of the average MI in the high-signal-to-noise ratio (SNR) regime. Theoretical analyses suggest that the average MI will converge its maximum as the SNR increases and the diversity order is the same as receive antenna number.

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